Network planning tool

ABSTRACT

Various embodiments provide a network planning tool comprising one or more memory storage areas containing data related to a plurality of transportation networks, and one or more computer processors configured to: receive input data comprising one or more modifications to one or more parameters associated with the plurality of transportation networks; retrieve at least a portion of the data contained in the one or more memory storage areas; validate the input data against the portion of data retrieved from the one or more memory storage areas, the validating comprising at least calculating one or more impacts to the integrated flow model based at least in part upon the received input data; and calculate, based at least in part upon the identified one or more impacts, one or more updated flow models for the plurality of transportation networks. Associated computer program products and computer-implemented methods are also provided.

CROSS-REFERENCE TO RELATED APPLICATIONS

This application claims priority to U.S. Provisional Application Ser.No. 61/534,094, filed Sep. 13, 2011, which is hereby incorporated hereinin its entirety.

BACKGROUND

Shipping carriers (e.g., common carriers, such as United Parcel Service,Inc. (UPS), FedEx, United States Postal Service (USPS), etc.) dailytransport millions of packages over tens of thousands of routes to andfrom a variety of clients for different purposes. Generally, shippingcarriers may reference and use multiple transportation networks tools tosimulate various shipment and load flow models based upon various datamaintained and stored within each of the tools. For an exemplary carriertracking more than 60,000 loads a day associated with nearly as manypieces of equipment and personnel, distributed across multiplegeographic area regions, accurate and efficient maintenance of flowplanning models becomes extremely complex. When changes, revisions,and/or updates occur, near real-time validation and optimization of suchagainst existing flow planning models across the multiple transportationnetwork tools is unfeasible. Thus, a need exists to provide a singletool to provide a simplistic network planning process that facilitatesnear real-time validation and optimization of changes to variousparameters across multiple transportation networks.

BRIEF SUMMARY

According to various embodiments of the present invention, a networkplanning tool is provided for simulating an integrated flow model for aplurality of transportation networks. Various embodiments of the networkplanning tool comprise one or more memory storage areas containing datarelated to a plurality of transportation networks, and one or morecomputer processors. The computer processors are configured to: (A)receive input data comprising one or more modifications to one or moreparameters associated with the plurality of transportation networks; (B)retrieve at least a portion of the data contained in the one or morememory storage areas; (C) validate the input data against the portion ofdata retrieved from the one or more memory storage areas, the validatingcomprising at least calculating one or more impacts to the integratedflow model based at least in part upon the received input data; and (D)calculate, based at least in part upon the identified one or moreimpacts, one or more updated flow models for the plurality oftransportation networks.

According to various embodiments of the present invention, a computerprogram product is provided comprising at least one computer-readablestorage medium having computer-readable program code portions embodiedtherein. The computer-readable program code portions comprise: a firstexecutable portion configured for receiving data associated with aplurality of transportation networks, wherein the data comprises a firstportion of existing data and a second portion of newly input data; asecond executable portion configured for validating the newly input dataagainst the existing data, wherein the validating comprises calculatingone or more impacts to an integrated flow model for the plurality oftransportation networks based at least in part upon the newly inputdata; and a third executable portion configured for using the one ormore impacts to the integrated flow model, the input data, and theexisting data to calculate one or more updated flow models for theplurality of transportation networks.

According to various embodiments of the present invention, acomputer-implemented method is provided for facilitating near real-timevalidation and optimization of an integrated flow model for a pluralityof transportation networks. Various embodiments of the method comprisethe steps of: (A) receiving and storing input data within one or morememory storage areas, the input data comprising one or moremodifications to one or more parameters associated with the plurality oftransportation networks; (B) retrieving from the one or more memorystorage areas at least a portion of previously existing data, thepreviously existing data also being associated with the plurality oftransportation networks; (C) validate, via at least one computerprocessor, the input data against the retrieved portion of existingdata, the validating comprising at least calculating, via the at leastone computer processor, one or more impacts to the integrated flow modelbased at least in part upon the received input data; and (D) calculate,via the at least one computer processor, one or more updated flow modelsfor the plurality of transportation networks, the one or more updatedflow models being based at least in part upon the identified one or moreimpacts.

BRIEF DESCRIPTION OF THE SEVERAL VIEWS OF THE DRAWING(S)

The accompanying drawings incorporated herein and forming a part of thedisclosure illustrate several aspects of the present invention andtogether with the detailed description serve to explain certainprinciples of the present invention. In the drawings, which are notnecessarily drawn to scale:

FIG. 1 is a block diagram of a system architecture 20 that may be usedin conjunction with a network planning tool according to variousembodiments;

FIG. 2 is schematic block diagram of a network planning tool server 200containing a network planning tool 201 according to various embodiments;

FIG. 3 illustrates an overall process flow for consolidated networkplanning via the network planning tool 201 according to variousembodiments;

FIG. 4 illustrates a schematic diagram of various databases that areutilized by the system architecture 20 shown in FIG. 1 according tovarious embodiments;

FIG. 5 is a schematic block diagram of the input module, the validationmodule, the optimization module, the decision support module, and thedistribution module shown in FIG. 2 according to various embodiments;

FIG. 6 illustrates a process flow for the input module shown in FIG. 2according to various embodiments;

FIG. 7 illustrates a process flow for the validation module shown inFIG. 2 according to various embodiments;

FIG. 8 illustrates a process flow for the optimization module shown inFIG. 2 according to various embodiments;

FIG. 9 illustrates a process flow for the distribution module shown inFIG. 2 according to various embodiments;

FIG. 10 illustrates a process flow for the decision support module shownin FIG. 2 according to various embodiments;

FIG. 11 is an exemplary screen display of a home screen 1100 of thenetwork planning tool according to various embodiments;

FIG. 12 is an exemplary screen display of a flow management screen 1200of an operator interface of the network planning tool according tovarious embodiments;

FIG. 13 is an exemplary screen display of a load management screen 1300of an operator interface of the network planning tool according tovarious embodiments;

FIG. 14 is an exemplary screen display of an input selection screen 1400of an operator interface of the network planning tool according tovarious embodiments;

FIG. 15 is an exemplary screen display of a change summary screen 1500of an operator interface of the network planning tool according tovarious embodiments;

FIG. 16 is an exemplary screen display of a decision support screen 1600of an operator interface of the network planning tool, as accessed froma load management screen of the network planning tool according tovarious embodiments;

FIG. 17 illustrates exemplary screen displays of a cost summary reportscreen 1700 and a load summary report screen 1710 of an operatorinterface of the network planning tool according to various embodiments;

FIG. 18 is an exemplary screen display of a facility summary reportscreen 1800 of an operator interface of the network planning toolaccording to various embodiments;

FIG. 19 is an exemplary screen display of an operations summary reportscreen 1900 of an operator interface of the network planning toolaccording to various embodiments; and

FIG. 20 is an exemplary screen display of exemplary printable charts2000 of an operator interface of the network planning tool according tovarious embodiments.

DETAILED DESCRIPTION OF VARIOUS EMBODIMENTS

Various embodiments of the present invention will now be described morefully hereinafter with reference to the accompanying drawings, in whichsome, but not all embodiments of the invention are shown. Indeed,embodiments of the invention may be embodied in many different forms andshould not be construed as limited to the embodiments set forth herein.Rather, these embodiments are provided so that this disclosure willsatisfy applicable legal requirements. Unless otherwise defined, alltechnical and scientific terms used herein have the same meaning ascommonly known and understood by one of ordinary skill in the art towhich the invention relates. The term “or” is used herein in both thealternative and conjunctive sense, unless otherwise indicated. Likenumbers refer to like elements throughout.

Apparatuses, Methods, Systems, and Computer Program Products

As should be appreciated, various embodiments may be implemented invarious ways, including as apparatuses, methods, systems, or computerprogram products. Accordingly, the embodiments may take the form of anentirely hardware embodiment, or an embodiment in which a processor isprogrammed to perform certain steps. Furthermore, variousimplementations may take the form of a computer program product on acomputer-readable storage medium having computer-readable programinstructions embodied in the storage medium. In such embodiments, anysuitable computer-readable storage medium may be utilized including harddisks, CD-ROMs, optical storage devices, or magnetic storage devices.

Various embodiments are described below with reference to block diagramsand flowchart illustrations of apparatuses, methods, systems, andcomputer program products. It should be understood that each block ofany of the block diagrams and flowchart illustrations, respectively, maybe implemented in part by computer program instructions, e.g., aslogical steps or operations executing on a processor in a computingsystem. These computer program instructions may be loaded onto acomputer, such as a special purpose computer or other programmable dataprocessing apparatus to produce a specifically-configured machine, suchthat the instructions which execute on the computer or otherprogrammable data processing apparatus implement the functions specifiedin the flowchart block or blocks.

These computer program instructions may also be stored in acomputer-readable memory that can direct a computer or otherprogrammable data processing apparatus to function in a particularmanner, such that the instructions stored in the computer-readablememory produce an article of manufacture including computer-readableinstructions for implementing the functionality specified in theflowchart block or blocks. The computer program instructions may also beloaded onto a computer or other programmable data processing apparatusto cause a series of operational steps to be performed on the computeror other programmable apparatus to produce a computer-implementedprocess such that the instructions that execute on the computer or otherprogrammable apparatus provide operations for implementing the functionsspecified in the flowchart block or blocks.

Accordingly, blocks of the block diagrams and flowchart illustrationssupport various combinations for performing the specified functions,combinations of operations for performing the specified functions andprogram instructions for performing the specified functions. It shouldalso be understood that each block of the block diagrams and flowchartillustrations, and combinations of blocks in the block diagrams andflowchart illustrations, could be implemented by special purposehardware-based computer systems that perform the specified functions oroperations, or combinations of special purpose hardware and computerinstructions.

Exemplary System Architecture 20

FIG. 1 is a block diagram of a system architecture 20 that can be usedin conjunction with various embodiments of the present invention. In atleast the illustrated embodiment, the architecture 20 may include one ormore distributed computing devices 100, one or more distributed handhelddevices 110, and one or more central computing devices 120, eachconfigured in communication with a network planning tool server 200 viaone or more networks 130. While FIG. 1 illustrates the various systementities as separate, standalone entities, the various embodiments arenot limited to this particular architecture.

According to various embodiments of the present invention, the one ormore networks 130 may be capable of supporting communication inaccordance with any one or more of a number of second-generation (2G),2.5G, third-generation (3G), and/or fourth-generation (4G) mobilecommunication protocols, or the like. More particularly, the one or morenetworks 130 may be capable of supporting communication in accordancewith 2G wireless communication protocols IS-136 (TDMA), GSM, and IS-95(CDMA). Also, for example, the one or more networks 130 may be capableof supporting communication in accordance with 2.5G wirelesscommunication protocols GPRS, Enhanced Data GSM Environment (EDGE), orthe like. In addition, for example, the one or more networks 130 may becapable of supporting communication in accordance with 3G wirelesscommunication protocols such as Universal Mobile Telephone System (UMTS)network employing Wideband Code Division Multiple Access (WCDMA) radioaccess technology. Some narrow-band AMPS (NAMPS), as well as TACS,network(s) may also benefit from embodiments of the present invention,as should dual or higher mode mobile stations (e.g., digital/analog orTDMA/CDMA/analog phones). As yet another example, each of the componentsof the system 5 may be configured to communicate with one another inaccordance with techniques such as, for example, radio frequency (RF),Bluetooth™, infrared (IrDA), or any of a number of different wired orwireless networking techniques, including a wired or wireless PersonalArea Network (“PAN”), Local Area Network (“LAN”), Metropolitan AreaNetwork (“MAN”), Wide Area Network (“WAN”), or the like.

Although the distributed computing device(s) 100, the distributedhandheld device(s) 110, the central computing device(s) 120, and thenetwork planning tool server 200 are illustrated in FIG. 1 ascommunicating with one another over the same one or more networks 130,these devices may likewise communicate over multiple, separate networks.For example, while the central computing devices 120 may communicatewith the network planning tool server 200 over a wireless personal areanetwork (WPAN) using, for example, Bluetooth techniques, one or more ofthe distributed devices 100, 110 may communicate with the networkplanning tool server 200 over a wireless wide area network (WWAN), forexample, in accordance with EDGE, or some other 2.5G wirelesscommunication protocol.

According to one embodiment, in addition to receiving data from thenetwork planning tool server 200, the distributed computing devices 100,the distributed handheld devices 110, and the central computing devices120 may be further configured to collect and transmit data on their own.Indeed, the distributed computing devices 100, the distributed handhelddevices 110, and the central computing devices 120 may be any deviceassociated with a carrier (e.g., a common carrier, such as UPS, FedEx,USPS, etc.). In various embodiments, the distributed computing devices100, the distributed handheld devices 110, and the central computingdevices 120 may be capable of receiving data via one or more input unitsor devices, such as a keypad, touchpad, barcode scanner, radio frequencyidentification (RFID) reader, interface card (e.g., modem, etc.) orreceiver. The distributed computing devices 100, the distributedhandheld devices 110, and the central computing devices 120 may furtherbe capable of storing data to one or more volatile or non-volatilememory modules, and outputting the data via one or more output units ordevices, for example, by displaying data to the user operating thedevice, or by transmitting data, for example over the one or morenetworks 130. One type of a distributed handheld device 110, which maybe used in conjunction with embodiments of the present invention is theDelivery Information Acquisition Device (DIAD) presently utilized byUPS.

Network Planning Tool Server 200

In various embodiments, the network planning tool server 200 includesvarious systems for performing one or more functions in accordance withvarious embodiments of the present invention, including those moreparticularly shown and described herein. It should be understood,however, that the control server 200 might include a variety ofalternative devices for performing one or more like functions, withoutdeparting from the spirit and scope of the present invention. Forexample, at least a portion of the server 200, in certain embodiments,may be located on the distributed computing device(s) 100, thedistributed handheld device(s) 110, and the central computing device(s)120, as may be desirable for particular applications.

FIG. 2 is a schematic diagram of the network planning tool server 200according to various embodiments. The network planning tool server 200includes a processor 230 that communicates with other elements withinthe server via a system interface or bus 235. Also included in thenetwork planning tool server 200 is a display/input device 250 forreceiving and displaying data. This display/input device 250 may be, forexample, a keyboard or pointing device that is used in combination witha monitor. The network planning tool server 200 further includes memory220, which preferably includes both read only memory (ROM) 226 andrandom access memory (RAM) 222. The server's ROM 226 is used to store abasic input/output system 224 (BIOS), containing the basic routines thathelp to transfer information between elements within the networkplanning tool server 200.

In addition, the network planning tool server 200 includes at least onestorage device or program storage 210, such as a hard disk drive, afloppy disk drive, a CD Rom drive, or optical disk drive, for storinginformation on various computer-readable media, such as a hard disk, aremovable magnetic disk, or a CD-ROM disk. As will be appreciated by oneof ordinary skill in the art, each of these storage devices 210 areconnected to the system bus 235 by an appropriate interface. The storagedevices 210 and their associated computer-readable media providenonvolatile storage for a personal computer. As will be appreciated byone of ordinary skill in the art, the computer-readable media describedabove could be replaced by any other type of computer-readable mediaknown in the art. Such media include, for example, magnetic cassettes,flash memory cards, digital video disks, and Bernoulli cartridges.

Although not shown, according to an embodiment, the storage device 210and/or memory of the network planning tool server 200 may furtherprovide the functions of a data storage device, which may storehistorical and/or current delivery data and delivery conditions that maybe accessed by the network planning tool server 200. In this regard, thestorage device 210 may comprise one or more databases. The term“database” refers to a structured collection of records or data that isstored in a computer system, such as via a relational database,hierarchical database, or network database and as such, should not beconstrued in a limiting fashion.

A number of program modules comprising, for example, one or morecomputer-readable program code portions executable by the processor 230,may be stored by the various storage devices 210 and within RAM 222.Such program modules include an operating system 280, an input module400, a validation module 500, an optimization module 600, a decisionsupport module 700, and a distribution module 800. Together, theseprogram modules define a network planning tool 201 according to variousembodiments. In these and other embodiments, the input module 400, thevalidation module 500, the optimization module 600, the decision supportmodule 700, and the distribution module 800 control certain aspects ofthe operation of the network planning tool 201 and thus the networkplanning tool server 200 with the assistance of the processor 230 andoperating system 280.

In general, as will be described in further detail below, the inputmodule 400 is configured to (i) receive, store, manage, and provide avariety of existing data associated with a shipping network and used togenerate a flow model thereof; and (ii) receive, store, and provide avariety of update data likewise associated with the shipping network andused to revise a flow model thereof. The validation module 500 isconfigured to activate a model validation tool, which calculates whetherthe input (e.g., updated) data results in any impacts to one or moreparameters of the flow model. Any identified impacted model data ispresented to a user of the tool and associated system 20. Theoptimization module 600 is then configured to activate a modeloptimization tool, which applies one or more algorithms to generate oneor more optimized models based upon the existing data, the input data,and the identified impacted data. The optimization module 600 may theneither display the one or more optimized models for user selection orautomatically select a single optimized model based upon predetermineduser parameters or otherwise. Once the single optimized model isselected, it is transmitted to the distribution module 800, whichactivates a distribution tool 810 to notify all networked devices (e.g.,devices 100, 110, 120, as previously described herein) of the updatedoptimization.

Where global optimization is not necessary and merely a single limitedmodification is required, the input module 400 may alternativelytransmit the update data and a limited data set to the decision supportmodule 700, which is configured generally to provide updated model databased for the limited change (e.g., bypassing a particular facility).Much like the optimization module 600, the decision support module 700then transmits the updated model data to the distribution module 800,which activates a distribution tool 810 to notify all networked devices(e.g., devices 100, 110, 120, as previously described herein) of theupdated optimization. Various embodiments of these modules and theirinteraction are described in more detail below in relation to FIGS.5-10.

In a particular embodiment, the program modules 400, 500, 600, 700, and800, are executed by the network planning tool server 200 and areconfigured to generate one or more graphical user interfaces accessibleto users of the network planning tool 201 and the system architecture 20associated therewith. Exemplary interfaces are described in more detailbelow in relation to FIGS. 11-20. In certain embodiments, the userinterfaces may be accessible via one or more networks 130, which mayinclude the Internet or other feasible communications network, aspreviously discussed. In other embodiments, one or more of the modules400, 500, 600, 700, and 800 may be stored locally on one or more of thedistributed computing devices 100, the distributed handheld devices 110,and/or the central computing devices 120, and may be executed by one ormore processors of the same. According to various embodiments, themodules 400, 500, 600, 700, and 800 may send data to, receive data from,and utilize data contained in, a database, which may be comprised of oneor more separate, linked and/or networked databases.

Also located within the network planning tool server 200 is a networkinterface 260 for interfacing and communicating with other elements ofthe one or more networks 130. It will be appreciated by one of ordinaryskill in the art that one or more of the network planning tool server200 components may be located geographically remotely from other networkplanning tool server 200 components. Furthermore, one or more of thenetwork planning tool server 200 components may be combined, and/oradditional components performing functions described herein may also beincluded in the network planning tool server 200.

While the foregoing describes a single processor 230, as one of ordinaryskill in the art will recognize, the network planning tool server 200may comprise multiple processors operating in conjunction with oneanother to perform the functionality described herein. In addition tothe memory 220, the processor 230 can also be connected to at least oneinterface or other means for displaying, transmitting and/or receivingdata, content or the like. In this regard, the interface(s) can includeat least one communication interface or other means for transmittingand/or receiving data, content or the like, as well as at least one userinterface that can include a display and/or a user input interface. Theuser input interface, in turn, can comprise any of a number of devicesallowing the entity to receive data from a user, such as a keypad, atouch display, a joystick or other input device.

While reference is made to a network planning tool “server” 200, as oneof ordinary skill in the art will recognize, embodiments of the presentinvention are not limited to traditionally defined server architectures.Still further, the system of embodiments of the present invention is notlimited to a single server, or similar network entity or mainframecomputer system. Other similar architectures including one or morenetwork entities operating in conjunction with one another to providethe functionality described herein may likewise be used withoutdeparting from the spirit and scope of embodiments of the presentinvention. For example, a mesh network of two or more personal computers(PCs), similar electronic devices, or handheld portable devices,collaborating with one another to provide the functionality describedherein in association with the network planning tool server 200 maylikewise be used without departing from the spirit and scope ofembodiments of the present invention.

According to alternative embodiments (not shown), components of the flowvalidation server may be located geographically remotely from othercomponents of the flow validation server. In addition, in accordancewith other embodiments (not shown), one or more of the components may becombined, and additional or fewer components performing functionsdescribed herein may be included in the flow validation server. Ofcourse, many other alternatives and architectures are possible and canbe used to practice various embodiments of the present invention.According to various embodiments, many individual steps of a process mayor may not be carried out utilizing the computer systems describedherein, and the degree of computer implementation may vary.

Network Planning Tool Server 200 Logic Flow

Reference is now made to FIGS. 3 and 5-10, which illustrate variouslogical process flows executed by various embodiments of the modulesdescribed above. In particular, FIG. 3 illustrates the overallrelationship of the modules 400, 500, 600, 700, and 800 of the networkplanning tool server 200, according to various embodiments. Asillustrated, operation of the network planning tool 201 and the systemarchitecture 20 associated therewith begins, according to variousembodiments, with the execution of the input module 400, whichdetermines the nature of the update necessary by newly input data (seeinput data 419 in FIG. 5). If a global model update is requested, theinput module 400 passes control to the validation module 500, and inturn to the optimization module 600. If a focused or limited update isall that is necessary, the input module 400 notifies the decisionsupport module 700, which is then executed to perform the limitedupdate, as appropriate. Once either global or limited updates arecompleted by the optimization module 600 and/or the decision supportmodule 700, control is passed to the distribution module 800. Stepsperformed by various embodiments of the input module 400 are describedin relation to FIG. 6; steps performed by various embodiments of thevalidation module 500 are described in relation to FIG. 7; stepsperformed by various embodiments of the optimization module 600 aredescribed in relation to FIG. 8; steps performed by various embodimentsof the distribution module 800 are described in relation to FIG. 9; andsteps performed by various embodiments of the decision support module700 are described in relation to FIG. 10.

As described in more detail below in relation to FIGS. 4 and 5, theinput module 400, according to various embodiments, retrieves existingmodel data 410 from one or more databases in communication with themodule 400. FIG. 4 illustrates a block diagram of various exemplarydatabases from which the input module 400 retrieves this information. Inparticular, in at least the embodiment shown in FIG. 4, the followingdatabases are provided: a service database 401, a transit database 402,a facility database 403, an equipment database 404, a personnel database405, a financial database 406, an operations database 407, and aflow/load database 408. Although the embodiment of FIG. 4 shows thesedatabases 401, 402, 403, 404, 405, 406, 407, 408 as being separatedatabases each associated with different types of data, but in variousother embodiments, some or all of the data may be stored in the samedatabase.

It should be appreciated that the various illustrated databases mayencompass data previously maintained by one or more separatetransportation network planning products, so as to facilitateconsolidation and integration of the same within the single networkplanning tool 201 and associated system architecture 20 describedherein. As a non-limiting example, the one or more databases describedherein may consolidate and integrate data previously accessible viamultiple transportation network systems (e.g., air versus groundtransportation, national versus international transportation, and thelike). Under prior configurations, if a user wished to, for example,analyze data related to particular services and also facilities,separate and often duplicative analyses were generally necessary. Stillfurther, the independent nature of such systems prevented seamlessintegration and optimization of changes made in each of thetransportation network systems. The unified network planning tool 201and associated system architecture 20 described herein provide a singletool to effectively and efficiently plan and execute all transportationnetworks and products together, at least in part, by consolidation of atleast the various non-limiting exemplary databases.

According to various embodiments, the service database 401 may beconfigured to store and maintain data related to the types a nature ofservice provided by a particular carrier-provider using the networkplanning tool 201 and associated system architecture 20. In certainembodiments, the service-related data may comprise at least deliverytype data (e.g., single day express, two day, three day, standard grounddelivery, standard freight, next day freight, deferred freight, etc.)and package type data (e.g., small package, standard package, oversizedpackage, freight, etc.). In these and still other embodiments, theservice-related data may also comprise data denoting availability of oneor more delivery type service, as described above, relative to one ormore transit routes, as defined and managed within the transit database402. As non-limiting example, the service-related data may indicateavailability of same day express delivery in a predominantly urban area,while not offering such in a predominantly rural and/or remote area. Avariety of alternatives could exist, as commonly known and understood inthe art. Still further, various embodiments of the service database 401comprise data related to service exceptions, as such may be generallydefined and/or predetermined for certain applications.

According to various embodiments, the transit database 402 may beconfigured to store and maintain data related to types of transitservices availability, along with details regarding respective variousroutes, whether by air, ground, water, or otherwise. In this manner, itshould be understood that the transit database 402 may consolidate avariety of transit-related data that may have previously been located inone or more of the distinct and separately maintained multipletransportation network systems. In certain embodiments, in addition toidentifying various routes by type, geography, and/or priority, thetransit database 402 may further identify availability of particularroutes, possible alternative flows and/or routes, along with varioustransit or route exceptions that may exist, comparable to the serviceexceptions previously described herein.

According to various embodiments, the facility database 403 may beconfigured to store and maintain data related to multiple facilitiesthrough which shipping service, transit, and/or operations are providedby a particular carrier-provider using the network planning tool 201 andassociated system architecture 20. The data may comprise informationregarding the type of facilities within the consolidated and integratednetwork (e.g., warehouse, service hub, airport, transit link, etc.), thecapacity of the facilities (e.g., flow volume on an equipment,personnel, or load basis, or otherwise), the real-time availability ofthe facilities (e.g., as based upon existing demands, etc.), and evenexceptions related to particular facilities (e.g., national holiday forfacility in Mexico which is not celebrated by, for example, related USfacilities). It should be understood, of course, that any of a varietyof facility related data may be collected and stored within the facilitydatabase 403 for use by the integrated network planning tool 201, as maybe desirable for particular applications.

According to various embodiments, the equipment database 404 may beconfigured to store and maintain data related to multiple pieces ofequipment utilized across the multiple transportation networks. Suchequipment may include, but is not limited to aircraft, vehicles, freightcontainers, forklifts, packaging materials, and the like. Theavailability of particular equipment, including exceptions thereto, asmay be predetermined according to various parameters, may also beincluded for purposes of modeling flow simulations of the transportationnetworks integrated within the network planning tool 201 and associatedsystem architecture 20. The personnel database 405 may be similarlyconfigured according to various embodiments and contain various datarelated to at least the number, the type, the location, theavailability, and the future needs of personnel necessary to maintainthe flow modeled across the multiple transportation networks via thenetwork planning tool 201.

According to various embodiments, the financial database 406 may beconfigured to store and maintain data related to costs andfinancial-related information for operation of the multipletransportation networks. Such data may include the non-limiting examplesof service cost data (e.g. actual shipping costs, charged shippingcosts, etc.), transit cost data (e.g., gas costs, vehicle maintenancecosts, driver salary costs, etc.), facility cost data (e.g., operationscosts, utility costs, personnel costs, etc.), and equipment cost data(e.g., maintenance, repair, replacement, etc.).

According to various embodiments, the operations database 407 may beconfigured to store and maintain data related to the operationallogistics of the multiple transportation networks integrated under theumbrella of the network planning tool 201 and associated systemarchitecture 20. In certain embodiments, the logistical related data mayinclude the non-limiting examples of shipping region maps, geographicalarea restrictions, holiday (or other) exceptions to logistical planningcalendars, regional regulations and standards that may impact transittime and/or other parameters, and any of a variety of exceptions, as maybe defined by one or more predetermined parameters or otherwise.

According to various embodiments, the flow/load database 408 may beconfigured to store and maintain data related to historical flow modelscreated, updated, validated, and/or optimized with the network planningtool 201 and associated system architecture 20. Such may informoptimization models produced via the tool 201 when applied to newlyinput data 419 (see FIG. 5), as will be described in further detailbelow. The flow/load database 408 may be further configured in certainembodiments to maintain and store various reports, charts, and summariesproduced by the network planning tool 201 or otherwise, for use asreference, when such may be desirable for particular applications.

According to various embodiments, any of the previously describeddatabases may be configured to store and maintain not only textuallybased data (e.g., cost figures, facility identification data, etc.), butalso graphically based data, such as the non-limiting examples ofgeographical area maps, designating not only service areas, but transitfacility hubs located and available therein and equipment dedicatedand/or available for use within particular areas. In this manner, thegraphically based data may be used to visually combine the datacontained within two or more databases, as illustrated in at least FIGS.11-12, as will be described in further detail below.

As an additional non-limiting example of the inter-relational nature ofthe various databases, in a particular embodiment, for each geographicalarea, time-in-transit data may be maintained and stored, including thenumber of days expected to transport a package from one shippingfacility to a particular destination. Transit data, when referenced forflow modeling purposes, may thus be informed not only by route distancedata maintained and stored within the transit database 403, but also byfacility related data maintained and stored within the facility database403, and even further by equipment or personnel related data maintainedand stored within the equipment and personnel databases 404, 405, andeven further by the operations database 407 information related toregional holidays, regulations, and/or standards that may influencetransit time calculations.

Exemplary System Operation

As indicated above, various embodiments of the network planning toolserver 200 execute various modules (e.g., modules 400, 500, 600, 700,800) to simulate and model distribution flows of a consignor's packagesfrom each of one or more hubs within the carrier's shipping network andfacilitate generation of an optimal network plan for the handlingthereof, taking into account a plurality of factors and considerations(e.g., data and information), as retrieved from the above-describedvarious databases and/or as provided by one or more users of the networkplanning tool 201 and/or the system architecture 20 associatedtherewith.

According to the embodiment shown in FIG. 5, the network planning toolserver 200 begins with the execution of the input module 400, whichretrieves, stores, and manages a myriad of data associated with theshipping network. When updates are made or new data is received, theinput module 400 is generally configured to determine whether the changerequires a global or a limited optimization of the network model. If aglobal model update is requested, the input module 400 passes control tothe validation module 500, and in turn to the optimization module 600.If a focused or limited update is all that is necessary, the inputmodule 400 notifies the decision support module 700, which is thenexecuted to perform the limited update, as appropriate. Once eitherglobal or limited updates are completed by the optimization module 600and/or the decision support module 700, control is passed to thedistribution module 800. Steps performed by each of these modules willnow be described in further detail.

Input Module 400

According to various embodiments, the input module 400 is configured toreceive, store, and maintain existing transportation network data 410.In certain embodiments, as may be understood from FIG. 5, the inputmodule 400 is configured to provide the existing data 410 to thevalidation module 500 and the optimization module 600. In at least oneembodiment, the input module 400 may be configured to provide at leastat least some portion of the data 410 to the decision support module700, as requested for population of a limited data set 705, as will bedescribed in further detail elsewhere herein.

FIG. 6 illustrates steps that may be executed by the input module 400according to various embodiments. Beginning with step 425, the inputmodule 400 assesses whether any input data 419 has been received by themodule. In certain embodiments, the input module 400 makes thisassessment by periodically scanning one or more databases associatedwith the module (e.g., see FIG. 4) and by identifying some portion ofdata within one or more of the databases that was not present during aprevious periodic scan under step 425. In various embodiments, if new orinput data 419 is identified, the input module 400 proceeds to step 435;otherwise the module proceeds into a static loop via step 430.

In various embodiments, the existing transportation network data 410comprises a variety of shipping and transportation related data locatedwithin one or more databases (see FIG. 4) and as previously describedherein. As illustrated in at least FIG. 5, however, the data 410 maycomprise the non-limiting examples of service data 411, transit data412, facility data 413, equipment data 414, financial data 415,personnel data 416, operations data 417, and shipping and transportationflow/load modeling data 418. In various embodiments, each of the piecesof the data 410 enable shipping carriers (e.g., common carriers, such asUnited Parcel Service, Inc. (UPS), FedEx, United States Postal Service(USPS), etc.) to monitor, maintain, and model various aspects ofmultiple package shipping and transportation processes. Notably, theinput module 400 of the network planning tool 201 provides a mechanismby which all of the data 410 is consolidated and available forintegration via any of the validation, optimization, and/or decisionsupport modules 500, 600, 700, as will be described in greater detailbelow.

In various embodiments, the input module 400 is further configured toreceive various pieces of input data 419. In certain embodiments, theinput data 419 may comprise any one of the non-limiting examples ofadding a new level of service to a particular geographically definedregion, opening a new transportation hub for a particular geographicallydefined region, reapportioning load volumes and routes associated withparticular geographically defined regions, and/or modifying anticipatedpackage volumes for particular geographically defined regions based uponfuturistic estimates. Of course, still other variations and types ofinput data 419 may be envisioned, as may be commonly known andunderstood in the context of system and flow modeling and simulationapplications.

Indeed, according to various embodiments, the input module 400 isconfigured in step 435 to assess whether the input data has global orlimited implications, relative to the multiple transportation networksintegrated within the network planning tool 201 and associated systemarchitecture 20. In certain embodiments, the assessment may be made byquerying a user of the tool whether a global or limited inquiry isdesired. In other embodiments, the assessment may be made internally tothe input module 400, whereby, for example, the input module may beconfigured to assess the content of the input data and automaticallyanalyze whether such is globally or locally focused in nature. In atleast one embodiment, such an assessment may be based upon historicaldata acquired and stored by the input module 400 during use over anextended period of time, while in still other embodiments such may beinformed, at least in part, by pre-established and/or predeterminedparameters.

Where a global inquiry is identified, the input module 400 is configuredto proceed to step 440, wherein a global data set 410 (e.g., comprisingthe various data 411-418 as previously described herein) are retrievedand provided, together with the global input data 419 to the validationmodule 500 for further processing, as will be described in greaterdetail below. Alternatively, where a limited inquiry is identified, theinput module 400 is configured to proceed to step 460, wherein only alimited data set 710 (e.g., comprising only a pertinent portion of thevarious data 411-418 as previously described herein) are retrieved andprovided, together with the limited input data 419 to the decisionsupport module 470 for further processing, as will be described ingreater detail below.

As a first non-limiting example of globally-focused data, which will becarried throughout herein, a user of the network planning tool 201 mayprovide input data 419 comprising an addition of an entirely new servicelevel, such as next day air service, to a geographical transit areapreviously defined as only having next day ground service, with onlystandard three day air service. Such an addition may be based upon, forexample, opening of a new air service terminal within the geographicaltransit area or the expansion of an existing terminal so as tofacilitate expanded service. Such input data 419 has the potential toimpact flow and planning data for the integrated multiple transportationnetworks in a global manner, and as such, the input module 400, uponassessing the same, is configured, in step 450 to provide the globallyfocused input data 419 (e.g., an addition of an entirely new servicelevel) to the validation module 500.

As a second non-limiting example of limited-focused data, which will bereturned to later herein in the context of describing the decisionsupport module 700, a user of the network planning tool 201 may provideinput data 419 comprising removing of a load from week 16 on a calendardue to, for example, illness and irreplaceability of a driver for theload. Recognizing the limited focus of such data, the input module 400may be, according to various embodiments, configured to provide such tothe decision support module 700 for focused analysis, as opposed to thevalidation module 500 for global analysis. Still other non-limitingexamples of limited focused input data 419 may comprise an inquiryregarding alternative flow paths for a particular package, impact to aparticular facility for a particular duration of time, impact of sortbypass, and/or lane enhancement inquiries, all as will be describedelsewhere herein in the context of the decision support module 700.

Validation Module 500

With reference to FIG. 7, according to various embodiments, thevalidation module 500 is configured to receive and/or retrieve globaldata 410 and input data 419 in step 520, after which the module proceedsin step 530 to activate a validation tool 510. The validation tool 510in certain embodiments is configured, as denoted by step 540, tocalculate impacted model data within the global data 410 containedwithin the various databases (see FIG. 4) of the multiple transportationnetworks integrated within the network planning tool 201.

Remaining with the previous non-limiting example of globally-focusedinput data 419, the validation tool 510 is configured to merge the inputdata 419 comprising addition of an entirely new service level (e.g.,next day air) with the existing global data 410, as retrieved from theinput module 400. As should be understood, the addition of an entirelynew service level will enable the particular geographical area toprovide a broader scope of service, such that, for example, air freightdeliveries previously limited to standard (e.g., three day) air deliverycould now possibly be transported in a more efficient and/or timelyfashion. As such, the model data, wherein a particular volume ofstandard air delivery and/or next day ground delivery data exists, maybe impacted, such that those volumes may be potentially adjustable basedupon the addition of a new service level. Alternatively, as yet anothernon-limiting example, consider wherein the input data 419 is the removalof a particular service level from a particular geographical region, inwhich case the model data would be potentially negatively impacted(versus the potentially positive impact resulting from a serviceaddition).

In either of the above-described non-limiting scenarios and still othersas may exist according to various embodiments, the validation module 500is configured, once impacted model data is identified in step 540 (seeFIG. 7), to store and display to a user the impacted model data in step550. Various illustrations of display screens accessible to a user ofthe network planning tool 201 are shown in FIGS. 11-13, wherein tabularsummary tables (e.g., 1110, 1210, and 1310), tabular detail tables(e.g., 1120, 1220, and 1320), and graphical geographical area maps(e.g., 1130, 1230, 1330) are provided for user manipulation and/orreference, all as will be described in further detail below.

Returning to FIG. 7, with continued reference to step 540, it should beunderstood that in various embodiments, the validation module 500 may beconfigured to automatically calculate impacted model data based at leastin part upon the retrieved global data 410 and the input data 419. Incertain embodiments, however, the validation module 500 may beconfigured to prompt a user of the network planning tool 201 to manuallyselect activation of the validation tool 510, as may be desirable forparticular applications, wherein for example, confirmation of the dataset being validated may be desirable. In still other embodiments, thevalidation module 500 may be alternatively configured when activatingthe validation tool 510, again as may be desirable for variousapplications.

According to various embodiments, as may be understood with reference toFIG. 7, the validation module 500 may, upon calculation of impactedmodel data in step 540 proceed further to step 550, wherein the impactedmodel data is stored (e.g., in one or more databases such as thoseillustrated in FIG. 4). In certain embodiments, the validation module500 may be further configured in step 550 to display the impacted datato a user of the network planning tool 201 for user viewing and/oranalysis thereof prior to transmittal of the same to the optimizationmodule 600 in step 560. In other embodiments, the validation module 500may merely display the impacted data for purposes of information (e.g.,not requiring any user action prior to proceeding further to, forexample step 560). In still other embodiments, the validation module 500may only store and not display the impacted model data at all, insteadproceeding directly to step 560, wherein control of the network planningtool 201 is inherently transferred to the optimization module 600 withthe transfer thereto of at least the impacted model data. In thismanner, various degrees of near-real-time validation (and/oroptimization) may be realized by various embodiments of the networkplanning tool 201, as compared to the iterative, complex, and oftentimesduplicative validation and optimization process of prior artconfigurations.

Optimization Module 600

With reference to FIG. 8, according to various embodiments, theoptimization module 600 is configured to receive and/or retrieve globaldata 410 and input data 419 in step 620 from the input module 400, alongwith impacted model data from the validation module 500 in step 630. Ofcourse, in certain embodiments, the global and input data may betransmitted to the optimization module 600 by the validation module 500as opposed to the input module 400, as may be desirable for particularapplications. In any of these and still other embodiments, however, itshould be understood that the optimization module 600 is configured instep 640 to activate an optimization tool 610 configured to execute oneor more algorithms upon the various retrieved and received data.

Remaining with FIG. 8, during step 650, upon activation of theoptimization tool 610 in step 640, the optimization module 600 proceedsto execute the one or more algorithms to identify one or more optimizedmodel results, based at least in part upon the impacted model data, theinput data 419, and the global data 410. In certain embodiments, thevarious executed algorithms may be configured to, for example, maximizecarrier profits, minimize carrier sort scans, minimize carriertime-in-transit, or the like, for load or packages identified within atleast the impacted model data. Returning for a moment to the previousnon-limiting examples of adding a particular service level from acertain geographical transit region, the optimization tool 610 may, inat least one embodiment, be configured to create new loads andessentially rebalance the new loads with previously existing loadswithin that geographical transit region so as to realize an optimalbenefit (e.g., maximum efficiency, handling, or the like) from the addedservice level. Alternatively, where a particular service level isremoved from the region, the optimization tool 610 may, in certainembodiments, be configured to rebalance existing loads so as toaccommodate packages and loads previously handled by the newly removedservice level.

Of course, according to various embodiments, any of a variety ofimpacted model data and/or input data 419 may be envisioned, in whichinstance, the optimization tool 610 is operatively configured to executeparticular ones of the various pre-configured algorithms, so as tooptimize the data model, as may be desirable for particularapplications. Indeed, various optimization algorithms exist, as commonlyknown and understood in the art, including the non-limiting examples ofthe simplex algorithm (as derived by George Dantzig and designed forlinear programming); quadratic algorithms, linear-fractional algorithms,network gradient algorithms, iterative methods (e.g., quasi-newtonmethods, interior point methods, pattern search methods, and the like),global convergence analyses, heuristic algorithms (e.g., memeticalgorithms, differential evolution, dynamic relaxation, particle swarmoptimization, and the like), and hub and feeder network optimizations(HFNOs). It should be understood, however, that still otherpossibilities exist, as the benefit provided by the network planningtool 201 is not merely an optimization algorithm, but the capability ofperforming near real-time validation and optimization upon multipleintegrated transportation networks, as previously described herein.

Returning now to FIG. 8, upon calculating one or more optimized modelresults in step 650, as based upon one or more optimization algorithmsas previously described herein, the optimization module is configuredto, in step 655, optionally display the one or more results to a user ofthe network planning tool 201, for user selection of a single optimizedmodel (see step 680), as may be desirable for particular applications.Indeed, the most desirable optimized model may, at least in part, dependupon particular parameters that may be known only to the user (e.g., notpreloaded or pre-established within the network planning tool 201according to certain embodiments). In other embodiments, of course, itshould be understood that the network planning tool 201 may bepre-configured to automatically select a more desirable optimized modelbased upon one or more predetermined and/or pre-established operatingparameters for the multiple integrated transportation networks. In theseand still other embodiments, the optimization module 600, instead ofproceeding to step 680, may proceed instead to step 660, wherein asingle one of the one or more optimized model results is selected.

With reference to our continuing non-limiting example, in the scenarioin which a user has added a new service level to a particulargeographical region, the optimization module 600 may return fivepossible optimized model results. One model may globally optimize byimposing an equal distribution of packages from each of the preexistingloads across all of the updated loads, including both those preexistingand those now available due to the new service level. Another model mayglobally optimize by targeting those previously stressed loads forredistribution and/or rebalancing with the newly available loads, whileleaving previously unstressed (e.g., low volume) loads unchanged. Stillother models may provide alternative options; however, it should beunderstood that each may involve varying degrees of efficiency and/orresulting balances of the integrated transportation networks, at leastsome of which may be less desirable than others for particularapplications. As such, where appropriate, the optimization module 600may provide the user with one or more selectable options for purposes ofoptimization (see, e.g., steps 655 and 680 of FIG. 8).

According to various embodiments, with reference further to FIG. 8, itshould be understood that once a single optimized model result isdetermined (e.g., whether automatically, manually, or otherwise, aspreviously described herein), the optimization module 600 is configuredto transmit at least the selected optimized model to the distributionmodule 800 for further processing, as will be described in furtherdetail elsewhere herein. In certain embodiments, the distribution of theoptimized model will ensure, at a minimum, near real-time update of theintegrated network planning model upon each of the various devices(e.g., 100, 110, 120, etc., each as illustrated in FIG. 1).

Decision Support Module 700

It should be understood that not all input data 419 received by theinput module 400 will implicate global-based impacts upon the multipletransportation networks integrated within the network planning tool 201.Indeed, as previously described herein, in certain embodiments, theinput data 419 may involve a limited or focused data set, in which casethe input module 400 is configured to transmit the same to the decisionsupport module 700 for further processing, as compared to thealternative validation module 500 and optimization module 600 processflows. At least one instance in which localized or focused optimizationmay be necessary is during the transition from planning to execution,wherein models may require tweaking given real-time impacts and/orchanges, thereby likewise requiring near or real-time validation andoptimization of required updates, much like that provided on the globalscale and as previously described herein.

With particular reference to FIG. 10, the decision support module 700 isconfigured according to various embodiments to receive a request for oneor more decision support calculations from the input module 400, asillustrated in step 720. Once received, the decision support module 700is configured in certain embodiments to retrieve certain pertinent datafrom the input module 400, as illustrated in step 730. In at least oneembodiment, the decision support module 700 may execute step 730automatically, while in other embodiments, some degree of user selectionof one or more data sets for retrieval may be involved, as may bedesirable for particular applications. In any of these and still otherembodiments, the retrieved data will comprise at least the input data419, as provided by a user of the network planning tool 201 to the inputmodule 400.

According to various embodiments, with reference momentarily to FIG. 5,the decision support module 700 may be configured to further retrieve,acquire, or otherwise receive a limited data set 705, which may includesome subset of the preexisting model data 410 associated with themultiple transportation networks integrated within the network planningtool 201. For example, in one embodiment, the limited data set 705 maycomprise data associated with just a particular load as it istransmitted via the one or more networks, wherein the input data 419 isconcerned with altering or modifying that load in some particularfashion. As another non-limiting example, in other embodiments, thelimited data set 705 may comprise data associated with a single facilityand the loads, equipment, personnel, etc. associated primarilytherewith, wherein the input data 419 seeks to alter or modify someaspect of operation for that single facility. What should be understood,is that the decision support module 700, in this manner, providesanalysis (e.g., validation and/or optimization modeling) on a smaller,more focused scale than the global validation and optimizationpreviously described herein, as in certain instances, such may bedesirable for particular applications.

Returning to FIG. 10, once the various pieces of focused data areretrieved or otherwise received by the decision support module 700, themodule proceeds to step 740, wherein a decision support tool 710 isactivated, as also illustrated in the exemplary user interface screen ofat least FIG. 16. The decision support tool 710 may be configured toprovide a user with various options, including those shown in FIG. 16,namely alternate flow analysis, bypass load analysis, bypass sortanalysis, bypass facilities analysis, and lane enhancement analysis. Asa non-limiting example, alternative flow analysis may be necessary wherea pre-established flow for a particular package becomes unfeasible,whether by impact, delay, or otherwise, in which case near real-timeanalysis of alternatives proves invaluable. For example, UPS freight forthe Denver Twilight to the Atlanta Night sort may be analyzed toidentify alternative flows that load to the Dallas Night, South Holland(Chicago) Night, or the Kansas City Sunrise flows, without impact tocommitments for the particular freight at issue.

Continuing with various non-limiting examples, bypass load analysis maysimilarly involve analysis of redistribution of loads within a singlefacility where, for example, a driver calls in sick and is unable toperform deliveries on Tuesday. When such is encountered, a user of thenetwork planning tool 201 may access the decision support module 700,whereby the decision support tool 710 is configured to execute one ormore validation and/or optimization algorithms (as described elsewhereherein) to determine one or more optimized model results for thelocalized data set. For example, the decision support tool 710 mayreturn a handful of possible optimization results wherein the packageson the undeliverable load are either evenly distributed across allremaining loads, or allocated to certain remaining loads based on anumber of factors, such as proximity of routes, load volume, and thelike. It should be understood, however, that in any of these and stillother embodiments, the decision support tool 710, regardless of whichanalysis is performed upon request, is configured, much like thevalidation and optimization tools 510, 610 described elsewhere herein toprovide near real-time validation and optimization of the impacted(albeit in this context limited) data set. In this manner, duplicative,complex, and oftentimes inefficient optimizations upon each of themultiple networks is avoided, via at least the integration thereofwithin a single network planning tool 201.

Distribution Module 800

According to various embodiments, with reference to FIG. 9, thedistribution module 800 is configured to receive optimized model datafrom either the optimization module 600 (see step 820) or the decisionsupport module 700 (see step 840), depending on whether the input data419 influencing the optimization is global or limited/focused in nature,as has been described elsewhere previously herein. In either scenario,however, it should be understood that the distribution module 800 isconfigured to ensure that the selected optimized model data is promptly,efficiently, and consistently distributed to each of the devices (e.g.,devices 100, 110, 120, etc., as illustrated in FIG. 1) in a nearreal-time fashion. In this manner, the network planning tool 201 isconfigured to not only provide near real-time validation andoptimization of the data within the multiple transportation networksintegrated within the tool, but also to ensure near real-timedistribution thereof across all interfaces with the networks. In otherwords, the network planning tool 201 provides both consistency andefficiency not only during the analysis and change-making process, butalso during the implementation thereof.

With continued reference to at least FIGS. 5 and 10, it should beunderstood that the distribution module 800 may be configured totransmit the optimized model data automatically, upon user prompt, orotherwise, as may be desirable for particular applications. In certainembodiments, the distribution module 800 may be further configured todisplay one or more summary reports to one or more users, as may be seenin at least the exemplary screen display 1500 of FIG. 15. In otherembodiments, one or more notifications may be generated by thedistribution module 800 upon transmittal of the optimized model data,thereby alerting (e.g., audibly, visually, via text or email orotherwise, etc.) users of the updates and/or changes being made acrossthe multiple integrated transportation networks of the carrier. Stillother embodiments may incorporate any of a variety of notification,alert, or updates to users, as commonly known and understood in the artand as may be desirable for particular applications.

Exemplary Operator/User Interface

Although various operator and user interfaces of the network planningtool 201 have been referenced previously herein, various exemplaryscreen displays are illustrated in at least FIGS. 11-20, each of whichwill be further described, in turn, below.

With reference to FIG. 11, an exemplary screen display 1100 of thenetwork planning tool 201 is illustrated. As may be seen, the screendisplay 1100 may comprise three general portions, namely a summary datatable 1110, a detailed data table 1120, and a graphical map 1130. Eachprovides integrated data for user manipulation and/or analysis. As anon-limiting example, consider the summary data table 1110, which may beconfigured to provide somewhat “high-level” data regarding a pluralityof loads within the one or more networks. To the right thereof (orotherwise configured in alternative embodiments), the detailed datatable 1120 provides additional detail regarding particular loadsselected by a user for additional evaluation, comparison, validation,and/or optimization. The graphical map 1130 provides a graphicalillustration of the loads selected and/or under evaluation, for purposesof visually considering the scope and content of the selected data,versus having such provided only in textual format.

FIG. 12 likewise illustrates an exemplary screen display 1200 of thenetwork planning tool 201, wherein transit flows may be analyzed, ascompared to the loads of display 1100. As may be seen, in certainembodiments, load flow may be viewed by day of the week, although inother embodiments, various alternative temporal restrictions may beselected, as may be desirable for particular applications. Summary,detailed, and graphical display portions (e.g., 1210, 1220, and 1230)are similarly provided according to various embodiments, although suchmay be customizable by a user, as desired, in which case the arrangementand/or display thereof may be altered from that particularly illustratedin exemplary FIG. 12.

FIG. 13 illustrates an exemplary screen display 1300 (likewise similarlyapportioned into segments 1310, 1320, 1330, like those for screens 1100and 1200 previously described herein), illustrating load editing optionswithin the network planning tool 201. As may be seen, a volumetricdifference between various loads may be displayed in the summary tableportion 1310, which data may be manipulated by editing destination andtransit information for particularly selected loads within the graphicalscreen 1330.

FIG. 14 illustrates an exemplary screen display 1400 which may beprovided as part of various embodiments of the network planning tool201. In certain embodiments, the screen 1400 may be an optionallyselectable wizard or “help” screen, while in other embodiments, thescreen 1400 may be configured as a “home” or start screen, wherein usersmay select one or more objectives or goals they would like to performand/or achieve within the network planning tool. As non-limitingexamples, as illustrated, the user may select to add, delete, modify, orcopy one or more loads, change flows of one or more loads, modify ordelete a sort requirement, edit characteristics for a particularfacility, add or remove a new service level, evaluate alternative flows,and/or modify volume data for various loads, facilities, or otherwise.According to various embodiments, selection of one or more of theoptions presented on the exemplary screen display 1400 may be referencedby the input module 400 to ascertain whether global or locally focusedvalidation and optimization is most appropriate. In this manner, inthese and other embodiments, the network planning tool 201 may beconfigured to logically determine the nature and scope of optimization,thereby facilitating automatic decision-making within the tool betweenthe alternative global and limited process flows, as previouslydescribed herein and illustrated in at least FIGS. 5-10.

FIGS. 15 and 17-20 illustrate a variety of report screens (e.g., 1500,1700, 1710, 1800, 1900) and/or printable charts (e.g., 2000) that may begenerated by the network planning tool 201. In certain embodiments, suchmay be generated by the distribution module 800, when notifying one ormore devices and/or users associated with the tool of optimized modeldata, while in other embodiments, the exemplary reports and/or chartsmay be generated by any of the various modules 400, 500, 600, 700,and/or 800, as appropriate and timely, during the course of an input,validation, and optimization process. For example, while the exemplarychange summary report 1500 may be generated and displayed to a userduring execution of the distribution module 800, it may be additionallyand/or alternatively generated and displayed during execution of thevalidation module, indicating, for example, to the user the load volumeand/or the financial impact due to particularly input changes. Likewise,according to various embodiments, cost and load reports 1700, 1710 maybe generated and provided to users during the execution of the inputmodule 400 so as to inform user decisions during validation andoptimization. The facility impact report screen 1800 and the holidayschedule report screen 1900 may also prove beneficial to generate andprovide to users, when changes to facilities and/or volumes committedthereto are being evaluated, validated, and/or optimized.

According to various embodiments, in addition to exemplary screenreports (as previously described) that may be provided for userreference, various charts may be provided for users to view and/orprint. As with the reports, such charts, as the exemplary sunrise,preload, and hub load charts 2000 of FIG. 20, may be provided to theusers during execution of any of the various modules 400, 500, 600, 700,and/or 800, as may be most appropriate for particular applications. As anon-limiting example, upon receipt of a distribution of newly optimizedmodel data via the distribution module 800, a user may generate andprint a set of updated charts, as revised based upon the newly optimizedmodel data. Other embodiments may be otherwise configured, as may bedesirable for various applications.

CONCLUSION

Many modifications and other embodiments of the invention set forthherein will come to mind to one skilled in the art to which thisinvention pertains having the benefit of the teachings presented in theforegoing descriptions and the associated drawings. Therefore, it is tobe understood that the invention is not to be limited to the specificembodiments disclosed and that modifications and other embodiments areintended to be included within the scope of the appended claims.Although specific terms are employed herein, they are used in a genericand descriptive sense only and not for purposes of limitation.

That which is claimed:
 1. A network planning tool for simulating anintegrated flow model for routing a plurality of packages within aplurality of transportation networks, the tool comprising: one or morememory storage areas containing data related to a plurality of existingloads contained within the plurality of transportation networks, theplurality of existing loads being balanced in a predetermined mannerrelative to one another; and one or more computer processors configuredto: (A) receive input data comprising one or more modifications to oneor more parameters associated with the plurality of transportationnetworks; (B) retrieve at least a portion of the data contained in theone or more memory storage areas; (C) validate the input data againstthe portion of data retrieved from the one or more memory storage areas,the validating comprising at least calculating one or more impacts tothe integrated flow model based at least in part upon the received inputdata; (D) determine, based at least in part upon the identified one ormore impacts, a plurality of updated flow models for the plurality oftransportation networks, said determination of the plurality of updatedflow models being based at least in part upon: where the one or moremodifications comprise an addition of a new service level alongside oneor more existing service levels, an addition of a new load within theplurality of transportation networks so as to accommodate the newservice level received and upon accommodation of the new service level arebalancing of the new load and the existing loads relative to oneanother, wherein the new and one or more existing service levels defineone or more handling parameters for transport of the plurality ofpackages; and where the one or more modifications comprise a deletion ofat least one of the one or more existing service levels, a rebalancingof the remaining existing loads relative to one another so as toaccommodate the one or more modifications received; (E) display, on auser interface of a first user device, at least one of the plurality ofupdated flow models for selection by a user; (F) receive, via the userinterface of the first device, an indication of a user selected updatedflow model; and (G) automatically generate and transmit instructionsconfigured to facilitate implementation of the user selected updatedflow model to a plurality of user devices either: where the one or moremodifications comprise the addition of the new service level, therebalancing of the new load and the existing loads relative to oneanother; or where the one or more modifications comprise the deletion ofthe existing service level, the rebalancing of the existing loadsrelative to one another so as to accommodate the one or moremodifications received.
 2. The network planning tool of claim 1, furthercomprising the step of updating the integrated flow model to reflect asingle one of the one or more updated flow models.
 3. The networkplanning tool of claim 2, wherein the one or more computer processorsare configured to provide real-time validation and optimization of theintegrated flow model for the plurality of transportation networks,based at least in part upon the calculation of the updated flow modelsfor the plurality of transportation networks.
 4. The network planningtool of claim 1, wherein the one or more computer processors areconfigured to automatically perform the recited steps based solely uponreceipt of input data in Step A.
 5. The network planning tool of claim4, wherein the one or more computer processors are configured to providereal-time validation and optimization of the integrated flow model forthe plurality of transportation networks, based at least in part uponthe calculation of the updated flow models for the plurality oftransportation networks.
 6. The network planning tool of claim 1,wherein: the input data comprises a global modification to one or moreparameters associated with the plurality of transportation networks; andthe portion of retrieved data previously stored comprises an entirety ofthe previously stored data.
 7. The network planning tool of claim 6,wherein: the global modification comprises a global addition of the newshipping service level within one or more of the plurality oftransportation networks; and the validation step comprises calculatingone or more impacts to the integrated flow model based upon the additionof the new shipping service level.
 8. The network planning tool of claim6, wherein: the global modification comprises a global deletion of thenew shipping service level within one or more of the plurality oftransportation networks; and the validation step comprises calculatingone or more impacts to the integrated flow model based upon the deletionof the new shipping service level.
 9. The network planning tool of claim8, wherein the calculation of one or more updated flow models comprisescalculating at least one flow model wherein one or more commitmentsassociated with the globally deleted service level are rebalancedbetween one or more remaining service levels so as to optimize theintegrated flow model for the plurality of transportation networks. 10.The network planning tool of claim 1, wherein the one or more computerprocessors are further configured to transmit the one or more updatedflow models to one or more distributed devices connected via at leastone network.
 11. The network planning tool of claim 10, wherein the oneor more computer processors are configured to automatically transmit theone or more optimized flow models to the one or more distributeddevices, so as to provide real-time updates based upon validation andoptimization of the plurality of transportation networks.
 12. Thenetwork planning tool of claim 1, wherein: the input data comprises alocalized modification to one or more parameters associated with theplurality of transportation networks; and the portion data retrievedfrom the one or more storage areas comprises a subset of the entirety ofthe data contained in the one or more storage areas, the subsetcomprising data associated with the one or more parameters beingmodified by the input data.
 13. The network planning tool of claim 12,wherein: the localized modification comprises bypass of a particularload within one or more of the plurality of transportation networks; andthe validation step comprises calculating one or more impacts to theintegrated flow model based upon the bypass of the particular load. 14.The network planning tool of claim 12, wherein the localizedmodification is selected from a group consisting of a bypass of aparticular load, a bypass of a particular facility, a bypass of aparticular sort, a lane enhancement, a change in service level, and analternative flow.
 15. The network planning tool of claim 12, wherein theone or more computer processors are further configured to automaticallytransmit the one or more updated flow models to one or more distributeddevices connected via at least one network.
 16. A computer programproduct comprising at least one non-transitory computer-readable storagemedium having computer-readable program code portions embodied therein,the computer-readable program code portions comprising one or moreexecutable portions configured for: receiving data associated with aplurality of existing loads contained within the plurality oftransportation networks, wherein the data comprises a first portion ofexisting data and a second portion of newly input data, and wherein theplurality of existing loads being balanced in a predetermined mannerrelative to one another; validating the newly input data against theexisting data, wherein the validating comprises calculating one or moreimpacts to an integrated flow model for the plurality of transportationnetworks based at least in part upon the newly input data; using the oneor more impacts to the integrated flow model, the input data, and theexisting data to determine a plurality of updated flow models for theplurality of transportation networks, said determination of theplurality of updated flow models being based at least in part upon:where the one or more modifications comprise an addition of a newservice level alongside one or more existing service levels, an additionof a new load within the plurality of transportation networks so as toaccommodate the new service level received and upon accommodation of thenew service level a rebalancing of the new load and the existing loadsrelative to one another, wherein the new and one or more existingservice levels define one or more handling parameters for transport ofthe plurality of packages; and where the one or more modificationscomprise a deletion of at least one of the one or more existing servicelevels, a rebalancing of the remaining existing loads relative to oneanother so as to accommodate the one or more modifications received;display, on a user interface of a first user device, at least one of theplurality of updated flow models for selection by a user; receive, viathe user interface of the first device, an indication of a user selectedupdated flow model; and automatically generating and transmittinginstructions configured to facilitate implementation of the userselected updated flow model to a plurality of user devices either: wherethe one or more modifications comprise the addition of the new servicelevel, the rebalancing of the new load and the existing loads relativeto one another; or where the one or more modifications comprise thedeletion of the existing service level, the rebalancing of the existingloads relative to one another so as to accommodate the one or moremodifications received.
 17. The computer program product of claim 16,further comprising a fourth executable portion configured to transmit atleast one of the one or more updated flow models for the plurality oftransportation networks to at least one distributed device.
 18. Thecomputer program product of claim 16, wherein the second and thirdexecutable portions are configured to provide real-time validation andoptimization of the integrated flow model for the plurality oftransportation networks, based at least in part upon the calculation ofthe updated flow models for the plurality of transportation networks.19. A computer-implemented method for facilitating real-time validationand optimization of an integrated flow model for routing a plurality ofpackages within a plurality of transportation networks, the methodcomprising the steps of: (A) receiving and storing input data within oneor more memory storage areas, the input data comprising one or moremodifications to one or more parameters associated with the plurality oftransportation networks; (B) retrieving from the one or more memorystorage areas at least a portion of previously existing data, thepreviously existing data also being associated with a plurality ofexisting loads contained within the plurality of transportationnetworks, the plurality of existing loads being balanced in apredetermined manner relative to one another; (C) validate, via at leastone computer processor, the input data against the retrieved portion ofexisting data, the validating comprising at least calculating, via theat least one computer processor, one or more impacts to the integratedflow model based at least in part upon the received input data; (D)determine, via the at least one computer processor, a plurality ofupdated flow models for the plurality of transportation networks, theone or more updated flow models being based at least in part upon theidentified one or more impacts, said determination of the plurality ofupdated flow models being based at least in part upon: where the one ormore modifications comprise an addition of a new service level alongsideone or more existing service levels, an addition of a new load withinthe plurality of transportation networks so as to accommodate the newservice level received and upon accommodation of the new service level arebalancing of the new load and the existing loads relative to oneanother, wherein the new and one or more existing service levels defineone or more handling parameters for transport of the plurality ofpackages; and where the one or more modifications comprise a deletion ofat least one of the one or more existing service levels, a rebalancingof the remaining existing loads relative to one another so as toaccommodate the one or more modifications received; (E) display, on auser interface of a first user device, at least one of the plurality ofupdated flow models for selection by a user; (F) receive, via the userinterface of the first device, an indication of a user selected updatedflow model; and (G) automatically generate and transmit instructionsconfigured to facilitate implementation of the user selected updatedflow model to a plurality of user devices either: where the one or moremodifications comprise the addition of the new service level, therebalancing of the new load and the existing loads relative to oneanother; or where the one or more modifications comprise the deletion ofthe existing service level, the rebalancing of the existing loadsrelative to one another so as to accommodate the one or moremodifications received.
 20. The computer-implemented method of claim 19,further comprising the steps of: updating the integrated flow model toreflect a single one of the one or more updated flow models; andtransmit, via the at least one computer processor, the single updatedflow model to one or more distributed devices connected via at least onenetwork.